Join NVIDIA's Infrastructure Specialists team to support customers in planning, designing, constructing, and deploying large-scale AI data centers (power, cooling, telemetry, controls, network/cabling, and physical infrastructure). The role requires at least 12 years of relevant experience, experience with hyperscale or high-density AI/HPC data centers, collaboration with product/engineering/partners, quality assurance, audits, and up to 25% travel. Base salary ranges provided for levels 5 and 6.

NVIDIA is hiring a Senior Data Backend Engineer to design and optimize microservices and distributed data pipelines that process large volumes of autonomous-vehicle (AV) data for AI training and data mining. Responsibilities include building streaming and resilient systems, workflow orchestration, security/authentication, logging, and deploying AI models (including RAG workflows). Required experience: MS +6 years or BS +8 years in a relevant technical field; strong skills with Python or Golang and technologies such as Kubernetes, Helm, Hive, Parquet, SQL, vector DBs (e.g., Milvus), ETL/big-data engines, and distributed systems. Base salary ranges provided (USD/year).

Provide primary technical support for a customer on NVIDIA Ethernet and AI infrastructure (including Spectrum-X). Responsibilities include diagnosing and resolving complex hardware and software issues on Linux (multi-distro), packet-level debugging (tcpdump/Wireshark), collaborating with Engineering/Marketing/Support, developing support methodologies, and participating in customer communications. Role requires at least 5 years of relevant support/debugging experience and regular travel to the Memphis, TN site.

NVIDIA seeks a Senior Developer Technology Engineer to research and develop GPU acceleration and low-level performance optimizations for deep learning, machine learning, and other AI domains. The role involves working with industry and academic experts to analyze and optimize complex algorithms on modern CPU and GPU architectures, publishing findings, and influencing hardware and software design. Requires an advanced computational degree (or equivalent experience), 5+ years' relevant experience, fluency in C/C++, and expertise in parallel programming and CPU/GPU architecture fundamentals.

Own and evolve CI systems that run ML workloads across GPUs and accelerators, improve reliability and reproducibility, apply automation and AI/agent-based workflows to reduce manual operations, and provide a self-service CI platform while partnering with compiler, infrastructure, and release teams. Requires 5+ years' experience and strong Python and CI/platform engineering skills.

Lead regional co-sell strategy and execution with major cloud service providers, build enablement, pipeline and GTM programs, and guide CSP onboarding and integration. Role requires 15+ years professional experience, 10+ years management experience, technical proficiency in HPC/cloud/AI/ML, and proven experience scaling partnerships across CSPs and ISVs in the EMEA region.

Role to engage payments developer ecosystems (payment networks, acquirers, issuers, FinTechs) to encourage adoption of NVIDIA AI/ML and computing platforms. Responsibilities include building technical expertise, integrating NVIDIA software (SDKs, tools, NIMs), supporting onboarding/integration, monitoring ecosystem trends, collaborating with partners and internal teams, and presenting at industry events. Requires 5+ years overall experience with 3+ years in financial services; hands-on AI/ML and cloud proficiency.

NVIDIA seeks a Senior SoC Subsystem & I/O Architect on the LPU team to convert product requirements into architecture and subsystem specifications for uncore, IO, memory, firmware-facing, boot/reset, safety, fault tolerance, diagnostics, and power subsystems. Responsibilities include specifying behavior for enumeration, capability discovery, configuration flows, memory sequence control, coherence, address mapping, interrupts, virtualization, error handling, and firmware-visible controls; building/maintaining functional and architectural models (C++, SystemC, Python) to validate intent before RTL/silicon; and driving tradeoffs across bandwidth, latency, power, area, timing, scalability, reliability, security, and debuggability. Requires 8+ years of SoC/subsystem/IO/interconnect architecture experience and strong collaboration and communication skills. Listed base salary ranges by level: 184,000–287,500 USD (Level 4) and 224,000–356,500 USD (Level 5).

The role is the technical focal point for GPU firmware and GPU system software working with CSP/hyperscale customers to ensure fleet-scale management, updates, and operation of NVIDIA GPU firmware. Responsibilities include driving firmware/software work streams with CSP engineering teams, gathering and synthesizing customer feedback into the feature roadmap, orchestrating large-scale firmware updates (multi-GPU sequencing, rollback, validation), and identifying cross-CSP issue patterns to improve documentation, tooling, and tests. Requires 15+ years in GPU system software/firmware/accelerator platform engineering and deep knowledge of GPU internals (VBIOS, InfoROM, microcontroller firmware, driver interactions), multi-GPU fabrics (e.g., NVLink), firmware lifecycle management, error handling and recovery, and GPU telemetry/health monitoring.

Principal Software Engineer partnering with CSP/hyperscale customers to characterize and improve end-to-end performance on NVIDIA platforms. Responsibilities include driving performance characterization and validation workstreams, maintaining and validating open-source stress/benchmark tools, synthesizing CSP feedback into optimization priorities (CUDA, NCCL, driver, firmware), and defining test strategies and tooling for certification and customer acceptance. Requires 15+ years in systems performance engineering and strong GPU profiling, distributed training performance, and data-analysis skills.

Senior technical lead responsible for rack-scale system SW/FW architecture and CSP engagements. Collaborates with cross-functional NVIDIA and CSP engineering teams to align on fabric management, multi-component firmware orchestration, health telemetry APIs, error handling/recovery, and serviceability; captures CSP feedback and drives integration readiness and tooling/test improvements. Role requires 15+ years in system software, platform firmware, or large-scale distributed systems.

Lead developer relations and technical partnership efforts for cloud hosting and AI Factory infrastructure: integrate NVIDIA software stacks, onboard partners, provide sample code and technical guidance, and coordinate feedback across product and engineering teams. Requires 12+ years in technology roles (software engineering, developer relations, solutions architecture, or similar) and 5+ years hands‑on experience with cloud hosting or AI Factory infrastructure, plus deep knowledge of Kubernetes, container runtimes, hypervisors, GPU acceleration (e.g., CUDA/DOCA), and related hardware and networking design.

Customer-facing role working with EDA/CAD developers, chip designers, equipment OEMs, and fabs to GPU-accelerate EDA and manufacturing workflows (place-and-route, simulation, DRC/LVS, verification, lithography), apply ML/DL for defect detection, metrology, and yield optimization, and collaborate with engineering and product teams to deliver trainings, demos, and technical guidance.

NVIDIA seeks a Field Applications Engineer to provide onsite technical engagement for large datacenter deployments of NVIDIA AI systems. Responsibilities include solving complex hardware and deployment issues, supporting sales account managers, establishing technical relationships with customer engineers and architects, identifying customer architectures and requirements, and providing technical training. Requires BS/MS in a technical field or equivalent, 5+ years in system design or technical customer support, and in-depth knowledge of servers, storage, and network hardware.

NVIDIA seeks a Senior Solutions Architect to work with CAE/CFD/FEA ISVs, simulation platforms, and industrial OEMs to accelerate solvers and engineering workflows using NVIDIA accelerated computing, Omniverse, and physics-ML. Requires MS/PhD or equivalent, 4+ years in computational engineering or solver development, and experience with GPU acceleration, numerical methods, Python/C/C++, HPC, and simulation tools.

Role focused on developing planet-scale maps from crowdsourced vehicle data: 3D reconstruction, structure-from-motion, pose estimation, multi-view geometry, map fusion and change detection. Requires strong C++ production engineering, experience with camera/video and sensor data (GPS/IMU, lidar, radar), and 15+ years of relevant experience.

Role focuses on developing large-scale mapping, 3D reconstruction, structure-from-motion, pose estimation, sensor fusion, map fusion, and change-detection algorithms and production C++ systems that transform multi-camera video and perception data from millions of vehicles into accurate maps for autonomous driving. Salary ranges provided (USD 152,000–241,500 for Level 3; USD 184,000–287,500 for Level 4).

Role requires owning product narratives, creating technically grounded content (blogs, whitepapers, web copy, demos), aligning sales and partners, and coordinating across engineering, product, marketing, and PR. Requires 8+ years in product marketing or product management for software/hardware, experience with scientific computing and AI, and domain experience in the climate and weather ecosystem.

Role involves simulating and testing full-scale network architectures, designing and implementing end-to-end automated tests and framework APIs in Python, performing system tests (regression, performance, functional, security), and reporting/debugging issues. Requires 5+ years in QA and/or networking, strong Python and Linux Bash skills, pytest and Playwright experience, and hands-on networking knowledge (switching/routing); virtualization and certifications (CCNA/ISTQB/LPIC-2) are advantageous.

Lead cross-functional coordination from early planning through bring-up, handover, and day-2 readiness for large-scale GPU/AI/data center systems. Requires 10+ years of customer-facing engagement leadership, technical depth in data center, HPC, networking, storage or cloud, strong risk and issue management, executive communication, and up to 25% travel.